mirror of
https://github.com/willnorris/imageproxy.git
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update all downstream dependencies
no specific features I'm looking to add, just keeping thing up to date. Unit tests and my manual testing seems like everything is still working as expected.
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25 changed files with 1661 additions and 486 deletions
148
vendor/github.com/disintegration/imaging/convolution.go
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148
vendor/github.com/disintegration/imaging/convolution.go
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package imaging
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import (
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"image"
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)
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// ConvolveOptions are convolution parameters.
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type ConvolveOptions struct {
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// If Normalize is true the kernel is normalized before convolution.
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Normalize bool
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// If Abs is true the absolute value of each color channel is taken after convolution.
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Abs bool
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// Bias is added to each color channel value after convolution.
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Bias int
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}
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// Convolve3x3 convolves the image with the specified 3x3 convolution kernel.
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// Default parameters are used if a nil *ConvolveOptions is passed.
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func Convolve3x3(img image.Image, kernel [9]float64, options *ConvolveOptions) *image.NRGBA {
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return convolve(img, kernel[:], options)
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}
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// Convolve5x5 convolves the image with the specified 5x5 convolution kernel.
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// Default parameters are used if a nil *ConvolveOptions is passed.
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func Convolve5x5(img image.Image, kernel [25]float64, options *ConvolveOptions) *image.NRGBA {
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return convolve(img, kernel[:], options)
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}
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func convolve(img image.Image, kernel []float64, options *ConvolveOptions) *image.NRGBA {
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src := toNRGBA(img)
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w := src.Bounds().Max.X
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h := src.Bounds().Max.Y
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dst := image.NewNRGBA(image.Rect(0, 0, w, h))
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if w < 1 || h < 1 {
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return dst
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}
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if options == nil {
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options = &ConvolveOptions{}
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}
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if options.Normalize {
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normalizeKernel(kernel)
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}
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type coef struct {
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x, y int
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k float64
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}
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var coefs []coef
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var m int
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switch len(kernel) {
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case 9:
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m = 1
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case 25:
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m = 2
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default:
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return dst
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}
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i := 0
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for y := -m; y <= m; y++ {
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for x := -m; x <= m; x++ {
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if kernel[i] != 0 {
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coefs = append(coefs, coef{x: x, y: y, k: kernel[i]})
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}
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i++
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}
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}
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parallel(h, func(partStart, partEnd int) {
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for y := partStart; y < partEnd; y++ {
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for x := 0; x < w; x++ {
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var r, g, b float64
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for _, c := range coefs {
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ix := x + c.x
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if ix < 0 {
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ix = 0
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} else if ix >= w {
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ix = w - 1
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}
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iy := y + c.y
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if iy < 0 {
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iy = 0
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} else if iy >= h {
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iy = h - 1
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}
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off := iy*src.Stride + ix*4
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r += float64(src.Pix[off+0]) * c.k
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g += float64(src.Pix[off+1]) * c.k
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b += float64(src.Pix[off+2]) * c.k
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}
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if options.Abs {
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if r < 0 {
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r = -r
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}
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if g < 0 {
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g = -g
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}
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if b < 0 {
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b = -b
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}
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}
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if options.Bias != 0 {
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r += float64(options.Bias)
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g += float64(options.Bias)
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b += float64(options.Bias)
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}
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srcOff := y*src.Stride + x*4
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dstOff := y*dst.Stride + x*4
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dst.Pix[dstOff+0] = clamp(r)
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dst.Pix[dstOff+1] = clamp(g)
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dst.Pix[dstOff+2] = clamp(b)
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dst.Pix[dstOff+3] = src.Pix[srcOff+3]
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}
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}
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})
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return dst
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}
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func normalizeKernel(kernel []float64) {
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var sum, sumpos float64
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for i := range kernel {
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sum += kernel[i]
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if kernel[i] > 0 {
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sumpos += kernel[i]
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}
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}
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if sum != 0 {
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for i := range kernel {
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kernel[i] /= sum
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}
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} else if sumpos != 0 {
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for i := range kernel {
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kernel[i] /= sumpos
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}
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}
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}
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